Agent Access Management
Agent access management is the practice of controlling what apps, data, and actions AI agents can access when acting on behalf of a user. It is the enforcement layer that sits between an agent's intent and the systems it interacts with, evaluating every request against policies defined by the organization.
Why It Matters
Traditional identity and access management was built for humans. A person authenticates, receives a role, and that role grants persistent permissions. Agents do not fit this model. They act on delegated authority, often across multiple systems in a single session, and the permissions they need change from task to task.
Agent access management addresses this gap by treating every agent action as a policy decision. Instead of granting broad roles, it evaluates each tool call at runtime: who is the user, what is the agent trying to do, which app is the target, and does the organization's policy allow it. The outcome is approve, escalate to a human, or deny.
This is distinct from the broader category of AI agent governance, which includes discovery, identity, and behavioral monitoring. Agent access management is narrower: it is the enforcement wedge that controls what agents are allowed to do, right now, in this session.